PARIS, FRANCE – I’m on my way to Dakar for the final week of iNERDE’s first STEM summer camp in Sénégal, held in cooperation with the Senegalese-American Bilingual School, SABS. I’ll be teaching the computer systems and computer science curriculum developed by iNERDE and helping to make our expansion to Senegal a success.
I’m travelling to Dakar by way of the northern franco-flemish city of Lille, France. I spent the last few days in Lille at the International Conference on Machine Learning, ICML, a gathering of the world’s top researchers in the science and mathematics behind artificial intelligence. Machine Learning is a revolution in the making, enabling computational devices to understand what they see, hear, and sense and to make decisions that can improve on human performance levels on the same tasks. One of the most dramatic examples of the use of this technology is self-driving cars; even I, as a computer scientist active in the field, did not realize how far along this technology is until a friend who works at Tesla took me for a ride down one of the busiest highways in Silicon Valley – without a driver.
I work for a company, Xilinx, that makes a kind of chip, an FPGA, that is used for machine learning. An FPGA is different from a CPU in being a flexible, reconfigurable, connected mesh of parallel computing elements – a bit like our brains, a flexible, reconfigurable, connected mesh of neurons. Parallel computing is the frontier of computer architecture, enabling us to create machines that are not only faster and more efficient than conventional CPUs at the stuff that computers do today, but also to create new uses of computers that can, like humans beings, deal with fuzzy information, make pretty good decisions based on what can be known, and can learn over time to make better decisions in the future. The old way of designing CPUs, the Von Neumann architecture, is about 75 years old. As exciting as the things we can do with machine learning are, for me, as a computer scientist, the most exciting thing is the fact that we are making an evolutionary leap in our understanding of how to build computers. Sometimes people worry that computers are getting too smart but it is actually human beings that are getting smarter, and have taught themselves to build exponentially on what we have learned. I felt in awe listening to artificial intelligence researchers at ICML sharing their profound knowledge and witnessing their passion for discovery.
I feel that my work for iNERDE is very related to my work on parallel computing. Both are ultimately about reaching the next level of human creativity. iNERDE is a passion for discovery of new educational paradigms. Like the Von Neumann architecture in computing, our modern educational systems have accomplished extraordinary things – but there is another level for us to aspire to. iNERDE, by choosing to begin its work in Africa, is also aiming at the next level in social evolution. We don’t accept the status quo of rich and poor nations. We think that every human being must have the right to the opportunity to develop her or his capacities, to create, and to contribute.
In the check-in queue at airport in Paris I felt myself already in Africa. It was chaos, of course, with everyone jostling to get into the line. It wasn’t aggressive, people were easy and friendly. I heard many languages all around, African languages I can’t recognize, parents speaking to their children in African-accented French and their kids responding in perfect Parisian French, and even Africans speaking unaccented American English. Many men and women were beautifully dressed in traditional African clothes.
At the security screening the agent looked at my ticket and said, “You’re going to Dakar! You’re going to love it, but it is really hot there! Where are you from? Oh, America! Los Angeles? I love America, I want to go to New York City and California and everywhere. Hey, cool mec! Welcome to Dakar!”